Researchers at NASA’s Jet Propulsion Laboratory in Pasadena, California put it to the test via a drone race — and the results may surprise you.

One competitor in NASA’s race was not a human, but rather a Google-funded drone controlled by artificial intelligence. The other was world-class drone pilot Ken Loo, known by many in the drone community as ‘FlyingBear.’

The two drone “pilots” raced through a twisting obstacle course. For the non-human drone, A.I. was used on three custom drones flown via algorithms that were integrated with Google’s Tango technology.

It turns out, the human and machine both won — for different reasons.

Loo, the human pilot, ultimately won for speed. Loo averaged 11.1 seconds per lap on the course, compared to the autonomous drones, which averaged 13.9 seconds. But the A.I. drone won in a measure of consistency.

“One of my faults as a pilot is I get tired easily,” Loo said. “When I get mentally fatigued, I start to get lost, even if I’ve flown the course 10 times.”

When his energy was fresh, Loo was able to it high speeds and perform corkscrews. But his times were also highly variable; the A.I. drone flew about the same race speed with every lap.

Off-the-shelf drones can fly autonomously today, but they mostly rely on GPS signals to navigate through space. However, GPS won’t work in most indoor spaces or in areas where GPS signals are weak.

Instead, the A.I. drones in this test rely on camera-based localization and mapping technologies to navigate through courses. While their likely isn’t much of a need for them in the world of drone racing, researchers say these drones could be able to help with use-cases like checking inventory in warehouses, assisting in search and rescue operations and maybe even navigating the corridors of a space station.